Combine two lists of dataframes, dataframe by dataframe

Question

I have what is no doubt a simple problem. I have spent the last hour or so looking around for a solution but am clearly missing something. If this is indeed a duplicate please link me to the right way to do this:

Example data:

names <- c("Cycling1.opr", "Cycling2.opr", "Cycling3.opr")
mydf1 <- data.frame(V1=c(1:5), V2=c(21:25)) 
mydf2 <- data.frame(V1=c(1:10), V2=c(21:30))
mydf3 <- data.frame(V1=c(1:30), V2=c(21:50))
opr <- list(mydf1,mydf2,mydf3)
mydf4 <- data.frame(timestamp=c(1:5))
mydf5 <- data.frame(timestamp=c(1:10))
mydf6 <- data.frame(timestamp=c(1:30))
timestamp <- list(mydf4,mydf5,mydf6)
names(opr) <- names
names(timestamp) <- names

Each list (opr and timestamp) always has the same number of data.frames and when having the same name, each of these data.frames is always the same length. What I would like to do is merge each similarly named dataframe into a single dataframe as part of a final list (perhaps named finalopr) such that its structure is as follows.

dput(finalopr)
list(structure(list(V1 = 1:5, V2 = 21:25, timestamp = 1:5), .Names = c("V1", 
"V2", "timestamp"), row.names = c(NA, -5L), class = "data.frame"), 
structure(list(V1 = 1:10, V2 = 21:30, timestamp = 1:10), .Names = c("V1", 
"V2", "timestamp"), row.names = c(NA, -10L), class = "data.frame"), 
structure(list(V1 = 1:30, V2 = 21:50, timestamp = 1:30), .Names = c("V1", 
"V2", "timestamp"), row.names = c(NA, -30L), class = "data.frame"))

Answer 1

> mapply(cbind, opr, timestamp, SIMPLIFY=FALSE)
$Cycling1.opr
  V1 V2 timestamp
1  1 21         1
2  2 22         2
3  3 23         3
4  4 24         4
5  5 25         5

$Cycling2.opr
   V1 V2 timestamp
1   1 21         1
2   2 22         2
3   3 23         3
4   4 24         4
5   5 25         5
6   6 26         6
7   7 27         7
8   8 28         8
9   9 29         9
10 10 30        10

$Cycling3.opr
   V1 V2 timestamp
1   1 21         1
2   2 22         2
3   3 23         3
4   4 24         4
5   5 25         5
6   6 26         6
7   7 27         7
8   8 28         8
9   9 29         9
10 10 30        10
11 11 31        11
12 12 32        12
13 13 33        13
14 14 34        14
15 15 35        15
16 16 36        16
17 17 37        17
18 18 38        18
19 19 39        19
20 20 40        20
21 21 41        21
22 22 42        22
23 23 43        23
24 24 44        24
25 25 45        25
26 26 46        26
27 27 47        27
28 28 48        28
29 29 49        29
30 30 50        30

Here's the structure:

> str(mapply(cbind, opr, timestamp, SIMPLIFY=FALSE))
List of 3
 $ Cycling1.opr:'data.frame':   5 obs. of  3 variables:
  ..$ V1       : int [1:5] 1 2 3 4 5
  ..$ V2       : int [1:5] 21 22 23 24 25
  ..$ timestamp: int [1:5] 1 2 3 4 5
 $ Cycling2.opr:'data.frame':   10 obs. of  3 variables:
  ..$ V1       : int [1:10] 1 2 3 4 5 6 7 8 9 10
  ..$ V2       : int [1:10] 21 22 23 24 25 26 27 28 29 30
  ..$ timestamp: int [1:10] 1 2 3 4 5 6 7 8 9 10
 $ Cycling3.opr:'data.frame':   30 obs. of  3 variables:
  ..$ V1       : int [1:30] 1 2 3 4 5 6 7 8 9 10 ...
  ..$ V2       : int [1:30] 21 22 23 24 25 26 27 28 29 30 ...
  ..$ timestamp: int [1:30] 1 2 3 4 5 6 7 8 9 10 ...